Computing movement speed

MovingPandas offers functions to compute and/or visualize the speed of movement along the trajectory between consecutive points.

import pandas as pd
import geopandas as gpd
from geopandas import GeoDataFrame, read_file
from shapely.geometry import Point, LineString, Polygon
from datetime import datetime, timedelta
import movingpandas as mpd

import warnings
warnings.filterwarnings('ignore')

print(f'MovingPandas version {mpd.__version__}')

MovingPandas version 0.8.rc1

Basic example

df = pd.DataFrame([
  {'geometry':Point(0,0), 't':datetime(2018,1,1,12,0,0)},
  {'geometry':Point(6,0), 't':datetime(2018,1,1,12,0,6)},
  {'geometry':Point(6,6), 't':datetime(2018,1,1,12,0,11)},
  {'geometry':Point(9,9), 't':datetime(2018,1,1,12,0,14)}
]).set_index('t')
gdf = GeoDataFrame(df, crs=31256)
toy_traj = mpd.Trajectory(gdf, 1)
toy_traj

Trajectory 1 (2018-01-01 12:00:00 to 2018-01-01 12:00:14) | Size: 4 | Length: 16.2m
Bounds: (0.0, 0.0, 9.0, 9.0)
LINESTRING (0 0, 6 0, 6 6, 9 9)

help(mpd.Trajectory.add_speed)

Help on function add_speed in module movingpandas.trajectory:

add_speed(self, overwrite=False)
    Add speed column and values to the trajectory's dataframe.
    
    Speed is calculated as CRS units per second, except if the CRS is geographic (e.g. EPSG:4326 WGS84)
    then speed is calculated in meters per second.
    
    Parameters
    ----------
    overwrite : bool
        Whether to overwrite existing speed values (default: False)

toy_traj.add_speed(overwrite=True)
toy_traj.df

	geometry	speed
t
2018-01-01 12:00:00	POINT (0.000 0.000)	1.000000
2018-01-01 12:00:06	POINT (6.000 0.000)	1.000000
2018-01-01 12:00:11	POINT (6.000 6.000)	1.200000
2018-01-01 12:00:14	POINT (9.000 9.000)	1.414214

We can also visualize the speed values:

toy_traj.plot(column="speed", linewidth=5, capstyle='round', legend=True)

<AxesSubplot:>

Real-world trajectories

gdf = read_file('../data/geolife_small.gpkg')
traj_collection = mpd.TrajectoryCollection(gdf, 'trajectory_id', t='t')

my_traj = traj_collection.trajectories[1]

my_traj.df

	id	sequence	trajectory_id	tracker	geometry
t
2009-06-29 07:02:25	1556	1090	2	0	POINT (116.59096 40.07196)
2009-06-29 07:02:30	1557	1091	2	0	POINT (116.59091 40.07201)
2009-06-29 07:02:35	1558	1092	2	0	POINT (116.59088 40.07203)
2009-06-29 07:02:40	1559	1093	2	0	POINT (116.59091 40.07200)
2009-06-29 07:02:45	1560	1094	2	0	POINT (116.59096 40.07198)
...	...	...	...	...	...
2009-06-29 11:09:47	2448	1982	2	0	POINT (116.32349 40.00037)
2009-06-29 11:09:57	2449	1983	2	0	POINT (116.32513 40.00057)
2009-06-29 11:10:02	2450	1984	2	0	POINT (116.32688 40.00087)
2009-06-29 11:10:07	2451	1985	2	0	POINT (116.32722 40.00101)
2009-06-29 11:13:12	2452	1986	2	0	POINT (116.32746 40.00052)

897 rows × 5 columns

Even if the GeoDataFrame does not contain a speed column, we can still plot movement speed:

my_traj.plot(column='speed', linewidth=5, capstyle='round', figsize=(9,3), legend=True, vmax=20)

<AxesSubplot:>

my_traj.hvplot(c='speed', clim=(0,20), line_width=7.0, tiles='StamenTonerBackground', cmap='Viridis', colorbar=True, width=500, height=300)

traj_collection.plot(column='speed', linewidth=5, capstyle='round',  legend=True, vmax=20)

<AxesSubplot:>